Object Detection Setup
by Ultralytics · open-source · Last verified 2026-03-17
Bootstraps a production-ready object detection workflow using YOLOv8 or RT-DETR, including webcam/video stream ingestion, NMS post-processing, and annotation overlay rendering. Outputs annotated frames and a structured JSON detections log suitable for downstream analytics.
https://github.com/ultralytics/ultralytics ↗B
B—Above Average
Adoption: AQuality: AFreshness: A+Citations: B+Engagement: F
Specifications
- License
- AGPL-3.0
- Pricing
- open-source
- Capabilities
- real-time-detection, multi-class-detection, video-stream-support, json-export
- Integrations
- ultralytics, opencv, supervision
- Use Cases
- retail-shelf-monitoring, traffic-analysis, warehouse-automation
- API Available
- Yes
- Language
- python
- Dependencies
- ultralytics, opencv-python, supervision, numpy
- Environment
- Python 3.10+, CUDA optional
- Est. Runtime
- Real-time or 1-5 minutes per video
- Tags
- object-detection, yolo, bounding-boxes, real-time, vision
- Added
- 2026-03-17
- Completeness
- 100%
Index Score
67.9Adoption
85
Quality
82
Freshness
90
Citations
70
Engagement
0